Paper Citation Record · LEDGER

Differentially Private Tabular Data Synthesis using Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.01457.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2406.01457 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:07:10.094727Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T20:18:55.673672Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 019f74d0-e446-44c4-98ab-bce324e3a3f3 · inbound

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? cites this paper.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? Differentially Private Tabular Data Synthesis using Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T15:07:10.094727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8983b170-f5b0-43dc-be2a-dfa185831ead · inbound

Clustering and Median Aggregation Improve Differentially Private Inference cites this paper.

Clustering and Median Aggregation Improve Differentially Private Inference Differentially Private Tabular Data Synthesis using Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T10:47:28.352313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ad9333f-307c-48b7-9377-a115628b40d8 · inbound

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data cites this paper.

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data Differentially Private Tabular Data Synthesis using Large Language Models

Reference 216

Resolution: unresolved; no resolver link, observed 2026-08-03T08:15:33.377042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aace993c-9769-414b-a5fa-31f92327453f · inbound

Generative AI and Federated Learning for Intrusion Detection Systems: A Survey cites this paper.

Generative AI and Federated Learning for Intrusion Detection Systems: A Survey Differentially Private Tabular Data Synthesis using Large Language Models

Reference 133

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:18:55.676013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.